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统计参数映射应用于大鼠在跑步机上行走时大脑激活的放射自显影研究。

Statistical parametric mapping applied to an autoradiographic study of cerebral activation during treadmill walking in rats.

作者信息

Nguyen Peter T, Holschneider Daniel P, Maarek Jean-Michel I, Yang Jun, Mandelkern Mark A

机构信息

Department of Physics and Astronomy, University of California, Irvine, CA, USA.

出版信息

Neuroimage. 2004 Sep;23(1):252-9. doi: 10.1016/j.neuroimage.2004.05.014.

Abstract

Autoradiographs are conventionally analyzed by a region-of-interest (ROI) analysis. However, definition of ROIs on an image set is labor intensive, is subject to potential inter-rater bias, and is not well suited for anatomically variable structures that may not consistently correspond to specific ROIs. Most importantly, the ROI method is poorly suited for whole-brain analysis, where one wishes to detect all activations resulting from an experimental paradigm. A system developed for analysis of imaging data in humans, Statistical Parametric Mapping (SPM), avoids some of these limitations but has not previously been adapted as a tool for the analysis of autoradiographs. Here, we describe the application of SPM to an autoradiographic data set mapping cerebral activation in rats during treadmill walking. We studied freely moving, non-tethered rats that received injections of the cerebral blood flow tracer [14C]-iodoantipyrine, while they were performing a treadmill task (n = 7) or during a quiescent control condition (n = 6). Results obtained with SPM were compared to those previously reported using a standard ROI-based method of analysis [J. Cereb. Blood Flow Metab. 23(2003) 925]. The SPM method confirmed most areas detected as significant using the ROI approach. However, in the subcortex, SPM detected additional significant regions that, because of their irregular structures, fell short of statistical significance when analyzed by ROI. The SPM approach offers the ability to perform a semi-automated whole-brain analysis, and coupled with autoradiography, provides an effective means to globally localize functional activity in small animals.

摘要

传统上,放射自显影片是通过感兴趣区域(ROI)分析来进行分析的。然而,在一组图像上定义感兴趣区域需要耗费大量人力,容易受到评分者间潜在偏差的影响,并且不太适合解剖结构可变的情况,因为这些结构可能与特定的感兴趣区域并不总是一致对应。最重要的是,感兴趣区域方法不太适合全脑分析,而在全脑分析中,人们希望检测由实验范式产生的所有激活。一种为分析人类成像数据而开发的系统——统计参数映射(SPM),避免了其中一些局限性,但以前尚未被改编为分析放射自显影片的工具。在此,我们描述了SPM在一个放射自显影数据集上的应用,该数据集用于绘制大鼠在跑步机行走过程中的脑激活情况。我们研究了自由活动、未系绳的大鼠,这些大鼠在执行跑步机任务(n = 7)或处于静止对照状态(n = 6)时接受了脑血流示踪剂[14C] - 碘安替比林的注射。将SPM获得的结果与先前使用基于标准感兴趣区域的分析方法所报告的结果进行了比较[《脑血流与代谢杂志》23(2003) 925]。SPM方法证实了使用感兴趣区域方法检测到的大多数显著区域。然而,在皮层下,SPM检测到了其他显著区域,由于其结构不规则,在通过感兴趣区域分析时未达到统计学显著性。SPM方法能够进行半自动全脑分析,并且与放射自显影相结合,为在小动物中全局定位功能活动提供了一种有效的手段。

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